Eucalyptus carbon income and expenditure estimation method and system based on full life cycle process

Abstract

The invention relates to a eucalyptus carbon income and expenditure estimation method and system based on a full life cycle process, and belongs to the field of forestry carbon neutralization. The method comprises the following steps: firstly, representing a cut and harvested forest product process based on a 3-PG model, and adding a forest product carbon emission module for representing forest product production, transportation, processing, use and waste based on a tracking bookkeeping method; secondly, based on eucalyptus sample plot data, the simulation performance of the improved 3-PG model is evaluated, and parameter correction is carried out; and finally, simulating the carbon income and expenditure process of the eucalyptus in the whole life cycle based on the verified improved 3-PG model. According to the method, sample plot scale and regional scale eucalyptus economic forest carbon income and expenditure simulation can be provided, the carbon reserve change process of the eucalyptus economic forest can be determined, and a prospective optimization strategy is provided for eucalyptus economic forest planting management and adjustment.

Description

Technical Field

[0001] The present invention belongs to the field of forestry carbon neutralization, and specifically relates to a method and system for estimating the carbon budget of eucalyptus based on the whole life cycle process. Background Art

[0002] Currently, the research on the carbon budget of eucalyptus economic forests either starts from the growth process of eucalyptus, studies the carbon fixation simulation in the growth stage, and emphasizes its carbon sink effect; or starts from the perspective of forest products, studies the carbon emission process of eucalyptus as forest products, and emphasizes its carbon source effect. The research results of these two categories cannot comprehensively reflect the carbon budget in the whole life cycle process of eucalyptus economic forests. The research on coupling the growth process and the carbon release process of forest products from the perspective of the whole life cycle and studying their carbon budget as a whole has not been reported yet, which limits our comprehensive understanding of the carbon sequestration capacity of eucalyptus economic forests. The main reason is that there is no method in the existing research methods that can deeply combine these two processes. As one of the main planted forest tree species, eucalyptus urgently needs to develop an integrated method to comprehensively and scientifically evaluate the carbon budget of its whole life cycle. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for estimating the carbon budget of eucalyptus based on the whole life cycle process, which can provide the simulation of the carbon budget of eucalyptus economic forests at the plot scale and the regional scale, help to clarify the change process of the carbon storage of eucalyptus economic forests, and put forward a forward-looking optimization strategy for the adjustment of the management of eucalyptus economic forests.

[0004] To achieve the above purpose, the technical solution of the present invention is: a method for estimating the carbon budget of eucalyptus based on the whole life cycle process, adding a forest product carbon emission module to the 3-PG model, and evaluating and calibrating the simulation performance of the improved 3-PG model to simulate the carbon budget process of the whole life cycle of eucalyptus; wherein, the forest product carbon emission module is defined as follows: (1) Carbon emissions during the growth process of eucalyptus Based on the 3-PG model, the loss of vegetation biomass caused by the roots, leaves and external factors of eucalyptus during the growth process of eucalyptus each month is released according to exponential decay, and the calculation method is as follows: is the carbon emission during the growth process of eucalyptus in the i th year, is the stock volume of forest products in the i th year, which is converted from the stem biomass estimated by the carbon fixation during the growth process of eucalyptus, D is the basic density of wood, CF is the carbon content coefficient of eucalyptus wood, HE is the harvest coefficient, is the decomposition coefficient, is the decomposition time; (2)Carbon emissions after eucalyptus logging (2.1)Carbon emissions from dead vegetation remaining on site after logging The dead vegetation remaining on site after logging, namely roots and leaves, will be decomposed for carbon emissions. The carbon emission process is the same as the growth process, showing exponential decay; (2.2)Carbon emissions during the transportation and processing of forest products after logging The energy consumption limit per unit product is used to estimate the carbon emissions during the transportation and processing processes. Different transportation methods and processing processes consume different types of energy, which are uniformly converted into standard coal. The carbon emission calculation is as follows: represents the carbon emissions during the transportation process in the i th year, CT represents the carbon emission coefficient during the wood transportation process, represents the carbon emissions caused by the processing process in the i th year, CP represents the carbon emission coefficient during the wood processing process; (2.3)Carbon emissions during the use and disposal of forest products after logging represents the carbon emissions during the use and disposal of forest products in the i th year, and respectively represent the carbon storage of the used products or the landfilled part of the wood forest products at the beginning of the i th year and the i th + 1 year; k is the decay constant under the first-order decay method, k =ln2 / tHL , where tHL is the half-life of the wood forest products; Inflow ( i ) is the carbon amount of the newly produced products or the carbon amount flowing into the solid waste landfill in the i th year; (3)Total carbon emissions represents the total carbon emissions in the i th year.

[0005] Furthermore, the method includes the following steps: S1. Check the format of the driving basic data, and estimate carbon fixation based on simulating the growth process of eucalyptus using the 3-PG model; S2. Add a forest product carbon emission module to the 3-PG model to obtain an improved 3-PG model; S3. Conduct parameter sensitivity analysis and parameter calibration of the improved 3-PG model at the plot scale or regional scale; S4. Simulate and estimate the carbon budget of the whole life cycle process of eucalyptus based on the baseline scenario or real scenario.

[0006] Furthermore, in S1, the driving basic data includes meteorological data, site conditions, and plot biomass. Among them, the meteorological data includes precipitation, temperature, and solar radiation, the site conditions include altitude, latitude, and soil fertility, and the plot biomass includes the basic biomass of different years.

[0007] Furthermore, in S1, estimating carbon fixation based on simulating the growth process of eucalyptus using the 3-PG model is as follows: S11. Net primary productivity represents j the net primary productivity during the growth process of eucalyptus in month both represent environmental factors, and the values are between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants; S12. Carbon fixation amounts of different organs where respectively represent j the carbon fixation amounts of the stem, root, and leaf of eucalyptus in month respectively represent the coefficients of net primary productivity allocated to the stem, root, and leaf, CF is the carbon content coefficient; S13. Total annual carbon fixation LVC all represents the total annual carbon fixation of eucalyptus, j represents the month, m represents the number of months.

[0008] Furthermore, the specific implementation of S3 is as follows: S31. Parameter sensitivity analysis The improved 3-PG model is divided into three parts: carbon fixation, carbon emission, and carbon budget. First, the Morris global sensitivity analysis method based on Bayesian statistics is used to conduct parameter sensitivity analysis on the results of carbon fixation, carbon emission, and carbon budget, and the parameters with greater influence on the output results are selected in each part of carbon fixation, carbon emission, and carbon budget. Then, the local sensitivity analysis method is used for calibration and verification. S32. Parameter calibration The fitting effect of the improved 3-PG model is evaluated by using the goodness of fit of the linear regression between the observed data and the simulated data of the stand indicators in the three parts of carbon fixation, carbon emission, and carbon budget. Three indicators, namely the coefficient of determination, root mean square error, and relative root mean square error, are used to evaluate the performance and accuracy of the improved 3-PG model in simulating stand growth.

[0009] The present invention also provides an eucalyptus carbon budget estimation system based on the whole life cycle process using the method as described above, including: A data input module for obtaining the driving basic data of the target research area, including meteorological data, site conditions, and plot biomass. An eucalyptus whole life cycle carbon fixation and carbon emission module for characterizing the carbon fixation and carbon emission during the growth process of eucalyptus, and accordingly divided into three carbon pools, namely the live vegetation carbon pool, dead vegetation carbon pool, and forest product carbon pool. A parameter sensitivity analysis and parameter calibration module for conducting parameter sensitivity analysis on the model to obtain the parameters with greater influence on the results, and performing calibration and verification to obtain the optimal parameters of the model. A carbon budget module for estimating the whole life carbon budget of eucalyptus by inputting the data in the data input module into the model with the optimal parameters obtained by the parameter sensitivity analysis and parameter calibration module, and outputting the corresponding carbon budget results of the target research area.

[0010] Furthermore, the eucalyptus whole life cycle carbon fixation and carbon emission module includes a carbon fixation module and a forest product carbon emission module, where the carbon fixation module is defined as follows: 1) Net primary productivity represents j the net primary productivity during the growth process of eucalyptus in month both represent environmental factors, and the values are between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants; 2) Carbon fixation amounts of different organs where respectively represent j the carbon sequestration amounts of the stem, root and leaf of eucalyptus in each month, respectively represent the coefficients of net primary productivity allocated to the stem, root and leaf, CF is the carbon content coefficient; 3) Total annual carbon fixation LVC all represents the total annual carbon fixation of eucalyptus, j represents the month, n represents the number of months.

[0011] Compared with the prior art, the present invention has the following beneficial effects: When calculating the carbon budget in the whole life cycle of eucalyptus, the present invention first simulates the growth process of eucalyptus economic forest based on the existing 3-PG model according to the input driving basic data such as meteorological and site conditions, secondly conducts module characterization on the production process of forest products felled from eucalyptus economic forest and subsequent transportation, processing, use and waste processes, then conducts parameter sensitivity analysis and calibration of the improved model at the plot scale (regional scale), and finally simulates and estimates the carbon budget in the whole life cycle of eucalyptus according to the actual situation or by setting different scenarios; The present invention can provide the simulation of the carbon budget of eucalyptus economic forest at the plot scale and the regional scale, helps to clarify the change process of the carbon storage of eucalyptus economic forest, and puts forward a forward-looking optimization strategy for the management adjustment of eucalyptus economic forest planting. Description of the Drawings

[0012] Figure 1 is a schematic diagram of the steps of the method for estimating the carbon budget of eucalyptus based on the whole life cycle process; Figure 2 is a module composition diagram of the system for estimating the carbon budget of eucalyptus economic forest based on the whole life cycle process; Figure 3 is a schematic diagram of the composition of a computer electronic device; Figure 4 is a specific flow chart for estimating the carbon budget in the whole life cycle of eucalyptus in this example. Detailed Embodiments

[0013] The technical solutions of the present invention will be specifically described below in conjunction with the drawings.

[0014] The present invention provides a method for estimating the carbon budget of eucalyptus based on the whole life cycle process. A forest product carbon emission module is added to the 3-PG model, and the simulation performance of the improved 3-PG model is evaluated and parameter calibrated to simulate the carbon budget process of the whole life cycle of eucalyptus. The main operation steps are as follows: First, based on the original 3-PG model, the process of logging and harvesting forest products is characterized, and a forest product carbon emission module based on the tracking accounting method for characterizing the production, transportation, processing, use, and disposal of forest products is added; Second, based on the eucalyptus plot data, the simulation performance of the improved 3-PG model is evaluated and parameter calibrated; Finally, based on the calibrated improved 3-PG model, the carbon budget process of the whole life cycle of eucalyptus is simulated.

[0015] As Figure 1 shown, in a preferred embodiment of the present invention, a method for estimating the carbon budget of eucalyptus economic forest based on the whole life cycle process is provided, and the steps include: S1. Obtain the meteorological data (including precipitation, temperature, solar radiation, etc.), site conditions (altitude, latitude, soil fertility, etc.), and plot biomass (as the basic biomass data for driving and for comparative verification) of the target research area. It should be noted that the collection methods, time, and spatial scales of meteorological data in different regions are different, and the meteorological data needs to be converted into data with a monthly step according to the simulation area. At the same time, the driving initial and verification biomass data of the simulation area need to be obtained according to the allometric growth equations of different regions.

[0016] In the embodiment of the present invention, first, the hourly precipitation (mm), temperature (°C), solar radiation (MJ / m -1 ), etc. data of the meteorological station are converted into monthly scale data. Secondly, the site conditions of the plot are input into the system in the format of a notepad. Finally, the root, stem, and leaf biomass (t / ha) is obtained through the allometric growth equation. Note that in addition to the initial biomass, the biomass of different years must also be calculated for subsequent comparative verification in the model simulation.

[0017] The method for estimating carbon fixation based on simulating the growth process of eucalyptus by the 3-PG model is as follows: 1.1) Net primary productivity represents j the net primary productivity during the growth process of eucalyptus in month both represent environmental factors, and the values are between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants; 1.2) Carbon fixation amounts of different organs wherein respectively represent j the carbon sequestration amounts of eucalyptus stems, roots and leaves in each month, respectively represent the coefficients of net primary productivity allocated to stems, roots and leaves, CF is the carbon content coefficient; 1.3) Annual total carbon fixation LVC all represents the annual total carbon fixation of eucalyptus, j represents the month, n represents the number of months; S2. Define the carbon emission module of eucalyptus forest products based on the simulated eucalyptus growth process (i.e., estimate carbon emissions), and the specific method is as follows: 2.1) Carbon emission settings in the eucalyptus growth process In the eucalyptus growth process, carbon emissions will occur due to root turnover, leaf litter and vegetation death caused by external factors. In this example, based on the root, leaf and vegetation biomass caused by external factors in each month simulated by the model, assuming that these lost biomass is released according to exponential decay, the calculation method is as follows: is the carbon emission in the eucalyptus growth process in the i th year, is the forest product stock volume (m i 3 ) in the D th year, which can be converted from the stem biomass in the carbon fixation part, -3 is the basic wood density (Mg / m CF is the carbon content coefficient of eucalyptus wood (m 3 ), HE is the harvest coefficient, is the decomposition coefficient, is the decomposition time; 2.2) Carbon emissions after eucalyptus logging (1) Carbon emissions from dead vegetation remaining on site after logging The dead vegetation (roots and leaves) remaining on site after logging will be decomposed for carbon emissions, and the carbon emission process is the same as the growth process, showing exponential decay.

[0018] (2) Carbon emissions during the transportation and processing of forest products after logging ​The transportation and processing of forest products will burn fossil fuels and emit greenhouse gases such as CO2. Different transportation methods consume different amounts of energy and release different amounts of greenhouse gases. In this process, the carbon emission factor per unit turnover of the road freight mode statistically reported by the national Ministry of Transport is used to calculate the carbon emissions in transportation. Different types of forest products have different processing processes, consume different types and amounts of energy, resulting in different carbon emissions. For example, the pulp production process consumes electricity, coal, etc., and the energy consumption is relatively high, while the sawn timber has a relatively small energy consumption. The present invention uses the energy consumption limit per unit product to estimate the carbon emissions in the processing process. Different transportation methods and processing processes consume different types of energy. The present invention uniformly converts them into standard coal. The carbon emission calculation is as follows: represents the carbon emissions during the transportation process in the i th year, CT represents the carbon emission coefficient during the transportation process of wood (t / m -3 ), represents the carbon emissions caused by the processing process in the i th year, CP represents the carbon emission coefficient during the wood processing process (t / m -3 ); (3) Carbon emissions during the use and disposal of forest products after logging represents the carbon emissions during the use and disposal of forest products in the i th year, and respectively represent the carbon storage of the used products or the landfilled part of the wood forest products at the beginning of the i th year and the i +1th year; k is the decay constant under the first-order decay method, k =ln2 / tHL , where tHL is the half-life of the wood forest products; Inflow ( i ) represents the iThe carbon amount of newly manufactured products or those flowing into solid waste landfills in a year; after the service life of forest products expires, they will be discarded or recycled. Generally, there are three treatment methods for discarded forest products, namely direct combustion, landfilling, and being piled on the ground. The carbon storage release situations of different treatment methods are different. Direct combustion will cause direct carbon release, while landfilled and open-air forest products release carbon into the atmosphere in the form of natural decomposition. In the present invention, the proportion of the discarded treatment methods of forest products is determined according to relevant literature materials, and the corresponding carbon storage changes are assigned. (a) Direct combustion: Forest products are divided into paper materials, wood-based panels, and sawn timber, and carbon is released according to the proportion of the combustion part in their respective discarded treatments; (b) Landfilling and open-air: The carbon in forest products in landfilling and open-air is released into the atmosphere in the form of natural decomposition. The natural decomposition here is represented by the first-order decay method during the use process of forest products to represent the carbon release from natural decomposition.

[0019] (4)Total carbon emissions Represents the total carbon emissions in the i-th year.

[0020] It should be noted that the parameters involved in the above-mentioned model need to be confirmed according to actual investigations, literature, etc., and the parameters should be localized to make the simulation effect better.

[0021] S3. Based on the improved 3-PG model (the improved 3-PG model is divided into three parts: carbon fixation, carbon emissions (equivalent to the carbon emissions module of forest products), and carbon budget), parameter sensitivity analysis and calibration of the model are carried out. The specific method is as follows: (1)Parameter sensitivity analysis Due to regional environmental differences or different provenances, some parameters may be different from the default values. Therefore, for different regions, some parameters need to be optimized and calibrated. The present invention uses the Morris global sensitivity analysis method based on Bayesian statistics to conduct parameter sensitivity analysis on the parameters, and it is divided into three parts. One part is to conduct parameter sensitivity analysis on the biomass of the diameter at breast height, roots, stems, and leaves during the growth process of eucalyptus before felling, that is, the parameter sensitivity analysis of the carbon fixation part; another part is to conduct parameter sensitivity analysis on the carbon emission parameters during the stages of dead vegetation and products after felling; the last part is to conduct parameter sensitivity analysis on the carbon budget of the entire process of eucalyptus. The final result takes the average of the sensitivity analysis results of the three parts to ensure the reliability of the sensitivity analysis. And select the parameters that have a greater impact on the output results of the above three parts, and use the local sensitivity analysis method to explore how to affect the output results of the model, further improving the credibility of the sensitivity analysis results. Finally, calibration and verification are carried out on this basis.

[0022] Bayesian statistical methods are based on the prior probability of the hypothesis, the probability of observing different data under a given hypothesis, and the observed data itself. The method is to combine the prior information about the unknown parameters with the sample information, and then, according to Bayes' formula, obtain the posterior information, and then infer the unknown parameters based on the posterior information. The calculation formula for its posterior probability is: In the formula is the prior distribution of the parameter, D is the observed data, is the prior parameter the probability of the distribution of the observed data in the distribution case, and is the parameter under the observed data posterior distribution.

[0023] The Morris sensitivity analysis method was first proposed by Max D. Morris in 1991. As a qualitative global sensitivity analysis, it gives the relative magnitude of the sensitivity of model parameters at a relatively low computational cost. It uses the elementary effect (EE) to judge the impact of parameter changes on the model operation results, so as to determine the sensitivity ranking of model parameters. The greater the mean value of the elementary effect of the model parameter, the higher the sensitivity of the parameter. Its calculation formula is as follows. In the formula is the elementary effect value of the i-th model parameter x 1 , x 2 , … , x m are the values of the model parameters; f () is the objective function. The present invention takes the average of the elementary effect values of all sample plots as the final result.

[0024] The local sensitivity analysis method uses the magnitude of the standardized sensitivity coefficient to represent the response of the model output result to the parameter.

[0025] where SSC represents the standardized sensitivity coefficient, which is used to represent the sensitivity of the model to this parameter. represents the model output varying with the parameter the absolute change amount, is the parameter change amount, the original model output value, It is the original parameter value. The present invention sets the ranges of multiple key parameters, all within ±25% based on the default values. All parameters are gradually changed in steps of 0.1%, and 1000 cycles are set to evaluate the influence laws of each parameter on the biomass of stems, roots, leaves, and the diameter at breast height.

[0026] (2)Parameter calibration To improve the performance and practicality of the model, the present invention calibrates 2 / 3 of the input data for the model and uses 1 / 3 for model verification. The present invention evaluates the fitting effect of the 3-PG model by using the goodness of fit of linear regression between the observed data and the simulated data of stand indicators such as the diameter at breast height, leaf biomass, root biomass, and stem biomass. Three indicators, the coefficient of determination (R2), the root mean square error (RMSE), and the relative root mean square error (RRMSE), are used to evaluate the performance and accuracy of the 3-PG model in simulating stand growth. The calculation formulas are as follows: Among them, is the observed data, is the average value of a series of observed data, is the predicted data, and n is the number of samples. The higher the R2, the smaller the RMSR and RRMSE, and the more accurate the model prediction. In addition, simple linear regression is used to evaluate the performance of the model related to the observation.

[0027] S4. Set the baseline scenario (real scenario) to simulate the carbon budget of the entire life cycle of Eucalyptus. The present invention provides different scenarios to simulate the carbon budget of Eucalyptus (obtained according to literature data, Eucalyptus cultivation regulations, and national forestry standards), and users can also set it directly. The baseline scenario (real scenario) provided by the present invention is shown in Table 4. The baseline scenario is a scenario set based on existing statistical data, while the experimental scenario is an experimental scenario set based on the baseline scenario under different planting designs, harvesting management, and forest product production configurations. Users can design the specific parameter values of the simulation scenario according to their needs.

[0028] The steps of the estimation classification method for the carbon budget of the entire life cycle of Eucalyptus shown in the above S1~S4 can essentially be implemented in the form of a computer program (in C++ version).

[0029] In addition, based on the same inventive concept, as Figure 2 shown, the present invention provides a system for characterizing the carbon budget of the entire life cycle of Eucalyptus based on an improved 3-PG model, which includes: A data input module for obtaining meteorological data (including precipitation, temperature, solar radiation, etc.), site conditions (altitude, latitude, soil fertility, etc.), and plot biomass (as the basic biomass data for driving and for comparison and verification) of the target study area; An eucalyptus whole-life cycle carbon fixation and carbon emission module for characterizing carbon fixation and carbon emission during the growth process of eucalyptus, and accordingly divided into three carbon pools, namely live vegetation carbon pool, dead vegetation carbon pool, and forest product carbon pool; A parameter sensitivity analysis and calibration module for performing parameter sensitivity analysis on the model to obtain parameters with greater influence on the results, and performing calibration and verification to obtain parameters suitable for the current situation and better simulation effects.

[0030] A carbon budget module for estimating the whole-life carbon budget of eucalyptus by inputting the data in the data input module into the model with the optimal parameters obtained through the parameter sensitivity analysis and parameter calibration module, and outputting the corresponding carbon budget results (plot scale (.xlsx) or spatial distribution map (.tif)) of the target study area.

[0031] Similarly, based on the same inventive concept, the present invention provides a computer program product, including a computer program / instructions, which when executed by a processor, can implement the method for estimating the carbon budget of eucalyptus economic forest based on the whole-life cycle process as described above.

[0032] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention.

[0033] Thus, based on the same inventive concept, the present invention provides a computer-readable storage medium corresponding to the method for estimating the carbon budget of eucalyptus economic forest based on the whole-life cycle process. A computer program is stored on the storage medium, and when the computer program is executed by a processor, it can implement the method and system for estimating the carbon budget of eucalyptus economic forest based on the whole-life cycle process as described above.

[0034] Thus, based on the same inventive concept, as Figure 3 shown, the present invention also provides a computer electronic device corresponding to the method for estimating the carbon budget of eucalyptus economic forest based on the whole-life cycle process provided in the above embodiment. It includes a memory and a processor; The memory is used to store a computer program; The processor is used to implement the eucalyptus economic forest carbon budget estimation method based on the full life cycle process as described above when executing the computer program; Specifically, in the computer-readable storage media of the above three embodiments, the stored computer program is executed by the processor, and the steps of S1 to S4 can be executed.

[0035] It can be understood that the above storage medium may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory. At the same time, the storage medium may also be various media such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disc that can store program codes.

[0036] It can be understood that the above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0037] In addition, it should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the above-described system can refer to the corresponding process in the foregoing method embodiments, and will not be described herein again. In the embodiments provided in the present application, the division of steps or modules in the system and method is only a logical function division, and there may be other division methods in actual implementation. For example, multiple modules or steps may be combined or integrated together, and a module or step may also be split. Embodiment

[0038] Next, the technical solution of the present invention will be clearly and completely described by taking the sample plot data of a forest farm in a certain province as an example for estimating the carbon budget of the whole life cycle of eucalyptus. The described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] In this embodiment, the specific process of an estimation method for the carbon budget of eucalyptus based on the whole life cycle is as follows Figure 4 as shown, and its steps include: Step 1: Obtain the meteorological data (including precipitation, temperature, solar radiation, etc.), site conditions (altitude, latitude, soil fertility, etc.), and plot biomass (basic biomass data as the driving force and for comparative verification) of the target research area.

[0040] In this embodiment, the research area is a plot in a forest farm in a certain province. The meteorological data is from the actual measurement of a certain meteorological station, and the site conditions are obtained from the plot survey. The plot biomass is estimated according to the allometric growth equation of local eucalyptus in a certain province.

[0041] First, convert the hourly precipitation (mm), temperature (°C), solar radiation (MJ / m -1 ) and other data of the meteorological station into monthly-scale data. Secondly, input the site conditions of the plot into the system in the format of a notepad according to the format. Finally, calculate the biomass of the root, stem and leaf (t / ha) through the allometric growth equation. Note that in addition to the initial biomass, the biomass of different years must also be calculated for subsequent comparative verification in the model simulation.

[0042] The biomass calculation formula is shown in Table 1: The method for estimating carbon fixation by simulating the growth process of eucalyptus based on the 3-PG model is as follows: 1.1) Net primary productivity represents j the net primary productivity during the growth process of eucalyptus in month both represent environmental factors, and the values are between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants; 1.2) Carbon fixation amounts of different organs Among them respectively represent j the carbon fixation amounts of the stem, root and leaf of eucalyptus in month respectively represent the coefficients of the net primary productivity allocated to the stem, root and leaf, CF is the carbon content coefficient; 1.3) Annual total carbon fixation amount LVC allRepresents the total annual carbon fixation of eucalyptus trees, j Represents the month, n Represents the number of months.

[0043] Step 2: Define the carbon emission process module of eucalyptus trees based on the simulated growth process of eucalyptus trees (i.e., estimate carbon emissions), and the specific method is as follows: 2.1) Carbon emission settings during the growth process of eucalyptus trees The calculation method of carbon emissions during the growth process of eucalyptus trees is as follows: Is the carbon emission during the growth process of eucalyptus trees in the i th year, Is the i th year's forest product stock volume (m 3 ), which can be converted from the stem biomass of the carbon fixation part and is an intermediate result value inside the model and is directly used as the input of this model, D Is the basic wood density (Mg / m -3 ), taking 0.5901, CF Is the carbon content coefficient of eucalyptus wood (m 3 ), taking 0.525, HE Is the harvest coefficient, which is deduced by the model itself, Is the decomposition coefficient, which has different values for different tree species. In this example, it takes 0.4853, Is the decomposition time; 2.2) Carbon emissions after felling eucalyptus trees (1) Carbon emissions from dead vegetation remaining on site after felling The dead vegetation (roots and leaves) remaining on site after felling will be decomposed for carbon emissions, and the carbon emission process is the same as the growth process, showing exponential decay.

[0044] (2) Carbon emissions during the transportation and processing of forest products after felling The carbon emission calculation is as follows: Represents the carbon emission during the transportation process in the i th year, CT Represents the carbon emission coefficient during the wood transportation process (t / m -3 ), taking 0.00010281, Represents the carbon emission caused during the processing process in the i th year, CP Represents the carbon emission coefficient during the wood processing process (t / m -3 ), and for wood-based panels, paper materials, and sawn timber, they take 0.17, 0.40, and 0.00187 respectively; (3) Carbon emissions from the use of forest products after felling Indicates the carbon emissions during the use and disposal of forest products in the i th year, and are respectively the carbon stocks of the products used or the wood forest products landfilled at the beginning of the i th year and the i +(1)st year; k is the decay constant under the first-order decay method, k =ln2 / tHL , where tHL is the half-life of wood forest products, and 20, 2, and 35 are taken for wood-based panels, paper materials, and sawn timber respectively; Inflow ( i ) is the carbon amount of the newly produced products or those flowing into the solid waste landfill in the i th year; CF is the carbon content coefficient of eucalyptus wood (m 3 ), and 0.525 is taken. In this example, the structural ratio of the carbon waste treatment method is paper materials, the combustion ratio is 0.08, and the open-air or landfill ratio is 0.92; the combustion ratios of wood-based panels and sawn timber are both 0.18, and the open-air or landfill ratio is 0.82.

[0045] (4) Total carbon emissions Indicates the total carbon emissions in the

[0046] th year. In the example, the model verification results of a certain forest farm also show higher simulation accuracy, and the simulation results are closer to the 1:1 line. The regression analysis of each growth index in the sample plot of a certain forest farm all passes the significance test (p<0.01). See Table 2. In the model calibration and verification stages, R 2 is between 0.92 and 0.99, and RRMSE is between 7.35% and 13.15%. Among them, the R2 values of stem, leaf, and aboveground biomass are increased by 0.03, 0.03, and 0.05 respectively, and the RRMSE values are decreased by 4.51%, 3.91%, and 4.45% respectively, indicating that the model has good predictive ability for the stand dynamics of this sample plot.

[0047] The important parameter table of carbon fixation and carbon emission, which is the carbon budget module of the entire life cycle process, is shown in Table 3 as follows: Step 4: Set the baseline scenario (real scenario) to simulate the carbon budget of the entire life cycle of eucalyptus (obtained according to literature, eucalyptus cultivation regulations, and national forestry standards), and users can also set it directly. The baseline scenario (real scenario) provided by the present invention is shown in Table 4. The baseline scenario is a scenario set based on existing statistical data. Users can design the specific parameter values of the simulation scenario according to their needs.

[0048] In this example, the eucalyptus plantation carbon budget under the baseline scenario shows a net carbon sequestration effect, and the carbon sequestration amount is 2.22×10 4 t / ha (Table 5). In the product structure of the baseline scenario, wood-based panels and sawn timber are the main sources of carbon sequestration, which are 0.53×10 4 t / ha and 1.76×10 4 t / ha respectively. While paper products show a net carbon emission characteristic under the baseline scenario, and its emission amount is 0.07×10 4 t / ha. This is mainly because the energy consumption and carbon emissions during the processing of paper products are relatively high, and the operating cycle is relatively short, and the carbon sequestration amount of vegetation growth is relatively small, resulting in a net carbon emission characteristic during this period.

[0049] The above are the preferred embodiments of the present invention. All changes made according to the technical solution of the present invention, when the functions and effects generated do not exceed the scope of the technical solution of the present invention, shall fall within the protection scope of the present invention.

Claims

1. A method for estimating the carbon budget of eucalyptus based on the whole life cycle process, characterized in that: A forest product carbon emission module was added to the 3-PG model, and the simulation performance of the improved 3-PG model was evaluated and the parameters were calibrated to simulate the carbon budget process of the entire life cycle of eucalyptus. The forest product carbon emission module is defined as follows: (1) Carbon emissions during eucalyptus growth Based on the 3-PG model, the monthly growth process of eucalyptus is simulated. The loss of vegetation biomass caused by the roots, leaves and external factors of eucalyptus is released according to exponential decay. The calculation method is as follows: For the i Carbon emissions from eucalyptus growth over the years, For the i The annual forest product stock is converted from the stem biomass in the carbon fixation estimation during the growth of eucalyptus. D is the basic density of wood, CF is the carbon content coefficient of eucalyptus wood, HE is the harvest coefficient, is the decomposition coefficient, To decompose time; (2) Carbon emissions after eucalyptus felling (2.1) Carbon emissions from dead vegetation left on site after felling The dead vegetation, i.e. roots and leaves, left on site after felling will decompose and release carbon. The carbon emission process is the same as the growth process, showing an exponential decay. (2.2) Carbon emissions from transportation and processing of forest products after logging The energy consumption limit per unit product is used to estimate the carbon emissions during the transportation and processing processes. Different transportation modes and processing processes consume different types of energy, which are uniformly converted into standard coal. The carbon emissions are calculated as follows: Indicates i Carbon emissions from transportation CT Indicates the carbon emission coefficient of the wood transportation process, Indicates i Carbon emissions from the processing process CP Indicates the carbon emission coefficient of wood processing; (2.3) Carbon emissions from the use and disposal of forest products after logging Indicates i Carbon emissions from the use and disposal of forest products and Respectively i Year and i +1 Carbon stocks of wood forest products used or abandoned to landfill at the beginning of the year; k is the attenuation constant under the first-order attenuation method, k =ln2 / tH ,in tH The half-life of wood forest products; Inflow ( i ) is the i The amount of carbon that is created in new products or goes to landfills each year; (3) Total carbon emissions Indicates i Total annual carbon emissions.

2. The method for estimating the carbon budget of eucalyptus based on the whole life cycle according to claim 1, characterized in that: The steps include: S1. Check the format of the driving basic data and estimate carbon fixation by simulating the growth process of eucalyptus based on the 3-PG model; S2, adding the forest product carbon emission module to the 3-PG model to obtain an improved 3-PG model; S3. Parameter sensitivity analysis and parameter calibration of the improved 3-PG model at the plot scale or regional scale; S4. Simulate and estimate the carbon budget of eucalyptus throughout its life cycle based on baseline scenarios or realistic scenarios.

3. The method for estimating the carbon budget of eucalyptus based on the whole life cycle according to claim 2, characterized in that: In S1, the driving basic data include meteorological data, site conditions, and sample plot biomass. The meteorological data include precipitation, temperature, and solar radiation; the site conditions include altitude, latitude, and soil fertility; and the sample plot biomass includes the basic biomass of different years.

4. The method for estimating the carbon budget of eucalyptus based on the whole life cycle according to claim 2, characterized in that: In S1, the carbon fixation estimation was performed based on the 3-PG model to simulate the growth process of eucalyptus, as follows: S11. Net primary productivity express j Net primary productivity of eucalyptus trees during growth in January, All represent environmental factors, with values ​​between 0 and 1; represents comprehensive physiological factors; represents the maximum canopy quantum efficiency, It indicates the effective photosynthesis absorbed by plants; S12. Carbon fixation in different organs in Respectively represent j Carbon sequestration in stems, roots and leaves of eucalyptus in July, represent the coefficients of net primary productivity allocated to stems, roots and leaves, respectively, CF is the carbon content coefficient; S13. Total carbon fixation per year LVC all represents the total carbon fixation of eucalyptus per year, j Indicates the month, m Indicates the number of the month.

5. The method for estimating the carbon budget of eucalyptus based on the whole life cycle according to claim 2, characterized in that: The specific implementation of S3 is as follows: S31. Parameter sensitivity analysis The improved 3-PG model is divided into three parts: carbon fixation, carbon emission and carbon budget. Firstly, the Morris global sensitivity analysis method based on Bayesian statistical method is used to analyze the parameter sensitivity of the results of carbon fixation, carbon emission and carbon budget, and the parameters with greater impact on the output results are selected. Then, the local sensitivity analysis method is used for calibration and verification. S32, parameter calibration The fitting effect of the improved 3-PG model was evaluated by using the linear regression goodness of fit between the observed data and simulated data of the three parts of forest stand indicators: carbon fixation, carbon emission and carbon budget. The performance and accuracy of the improved 3-PG model in simulating forest stand growth were evaluated using three indicators: determination coefficient, root mean square error and relative root mean square error.

6. A eucalyptus carbon budget estimation system based on the whole life cycle process using the method as claimed in claim 1, characterized in that: include: Data input module, used to obtain driving basic data of the target study area including meteorological data, site conditions, and biomass of the sample plot; Eucalyptus full life cycle carbon fixation and carbon emission module, used to characterize the carbon fixation and carbon emission during the growth process of eucalyptus, which is divided into three carbon pools: living vegetation carbon pool, dead vegetation carbon pool and forest product carbon pool; Parameter sensitivity analysis and parameter calibration modules are used to perform parameter sensitivity analysis on the model to obtain the parameters that have a greater impact on the results, and to calibrate and verify to obtain the optimal parameters of the model; The carbon budget module is used to estimate the carbon budget of eucalyptus throughout its life cycle by using the model with the optimal parameters obtained by the parameter sensitivity analysis and parameter calibration module of the data input into the data input module, and output the carbon budget results corresponding to the target study area.

7. The eucalyptus carbon budget estimation system based on the whole life cycle process according to claim 6, characterized in that: The eucalyptus life cycle carbon fixation and carbon emission module includes a carbon fixation module and a forest product carbon emission module, where the carbon fixation module is defined as follows: 1) Net primary productivity express j Net primary productivity of eucalyptus trees during growth in January, All represent environmental factors, with values ​​between 0 and 1; represents comprehensive physiological factors; represents the maximum canopy quantum efficiency, It indicates the effective photosynthesis absorbed by plants; 2) Carbon fixation in different organs in Respectively represent j Carbon sequestration in stems, roots and leaves of eucalyptus in July, represent the coefficients of net primary productivity allocated to stems, roots and leaves, respectively, CF is the carbon content coefficient; 3) Total carbon fixation per year LVC all represents the total carbon fixation of eucalyptus per year, j Indicates the month, n Indicates the number of the month.

Images